What It Means to be in the 1% Across the US

welcome to Windfall's webinar series. We are talking about what it means to be in the top one percent across the United States today. This is a twenty twenty six update. If you have not heard about Windfall or this is one of your first time joining a webinar, that will come up just in a couple of slides. But before I get started, I'll just introduce myself real quick. My name is Arup Banerjee. I'm the CEO and cofounder of Windfall. If you're not familiar with our company, we have some of our stats over on the right hand side here. Really, we're talking more about affluent US households today. We define that over a million dollars in net worth. Obviously, we're taking a look at the one percent as well, so there's a little bit more that goes beyond that. But I'm put my email address right here. If you have any questions after the webinar or have any additional comments, feel free to send me a note or use the q and a button here. We will be going through that momentarily. Before I go to today's agenda, though, I'm gonna actually start us off with a poll question, which is why did you join this webinar? Because there's a lot of information, real cool things that we're actually gonna be talking about, but this would be helpful. And it is multiple selections, so it could be all of the above. But, really, is it about learning about the macro, understanding where wealth is going, you know, trying to understand strategies holistically? So take a moment, and I'll leave that up there as we go through today's agenda. So for today's agenda, as I mentioned, we're doing a quick windfall overview. Really, the crux of the conversation is gonna be around what it means to be in the top one percent. We will talk a little bit about some of these strategies that I put up here. And, if we have some time, I'll I'll make sure that we go through a demo and saving anything for a q and a. So, again, use that q and a. I'll try and go through the slides appropriately, but this is a sneak preview. If you're on this webinar, this information, this content has not been released to anybody. We're actually going to be publishing our blog post and a press release in a couple days here. So this is gonna be great for y'all just to get some bonus information on top of it. So I'll share the poll results here just real quick. It looks like a lot of folks just trying to understand that the current approach as well as gaining strategies would be helpful in making sure that it's actionable. So we will certainly waive those in as well. I always like to go through, an overview of what we are gonna go through on top of the agenda just to make sure. So we will do a little bit of windfall. It won't be a full commercial here, but I do wanna go through some of that. I'll give you a brief on the macro as well as given the consumer economy, what it means in that top one percent, but there's gonna be some bonus material here that we'll actually go through in specific states, in specific asset classes, things of that nature, and, of course, those strategies. So I'll show you also a new product that we released about two weeks ago, as part of the demo today, so we'll at least, go through that. And what we won't necessarily go through is how we specifically build our data. I'll talk about that at a high level, or all the products and services that we, solve for and, ultimately, how this could actually work with you. Of course, again, my email address, Roop at windfall dot com. Happy to talk to you guys after, the the webinar as well. Okay. Awesome. So let's jump into, you know, a a quick windfall overview, but I wanna set the stage here because I'm gonna start utilizing some of this type of, language throughout the the webinar. So the the next poll that I have here is specifically around, are you currently using any third party data? So I'll stop sharing the prior poll, and I'll pull up this other one. In terms of, you know, third party data and just to explain that, that's an external data source. So it's a data that you license and bring into your CRM, or you might bring into an AI system or into, you know, leveraging APIs holistically. There could be a lot of different ways to do it. So I do see folks are going through, and it looks like the majority are at least using at least one, if not two or three data sources here as well. So, I'll go ahead, and I will share those results, just so folks can take a look there as well. But the majority are using at least one data source. Okay. Cool. So now when we think about high net worth, ultra high net worth, when we determine if your data is up to date, we're talking about what the top one percent is today. Now if you looked in January, if you looked in, February, March, and April, the number will be different across the board. And it really matters a little bit further because as we just talked about third party data, this was actually pretty interesting for me to take a look at. This is the interest over time according to Google, Ngram search. And so data enrichment, as you can see with the rise of AI and also if you think about third party data, this has really started to peak in terms of where folks are trying to fit in. Now Windfall, we've been around since twenty sixteen, so almost ten years here, and our vision, is really to democratize access workflows and insights on people. Why we call it people data versus wealth data only is that we do have other data points outside of wealth, including things like careers. Right? All of us on this call most likely, are professionals, and so we wanna marry that altogether, to really think about your consumer profile as well as your career profile in one dataset called people. Now why do we get started to even begin with? Well, when we started looking at even the consumer space and the wealth space, well, if you look at net worth, a lot of the folks in the past had these really broad ranges, one to a hundred million dollars, or they would cap out at two million dollars. So in that scenario, right, Elon Musk would be worth two million dollars. Well, okay. Great. We can use things like household income or home value, but we're located we're headquartered in San Francisco. We also have an office in Denver. Like, if you use just those two components and then you look at other places in the country, that's gonna be really off. And so, ultimately, organizations have to start doing that. On the prior slide, you know, where it said, hey. Are you a good data expert or not? Well, you kinda have to be today, or you have to really make sure that you're choosing the right partners to to take a look at. Now why do some of these solutions miss the mark? We we actually have done this on a couple of other webinars in the past, but just to kinda make sure, is that just imagine you had Jane Smith, and we're looking at somebody who's a, you know, legacy, data vendor versus, you know, somebody in reality. Well, if you're just scanning this and look at the first three, it looks pretty good up until you get to net worth. And in fact, about fifty percent of this data is inaccurate. Now, ultimately, why is that the case? Well, a lot of these folks rely on survey or census data. Just because we're in the Bay Area, just because we have high income, right, you're gonna correlate that with affluence. Probably is not true. I'm very different than my neighbor who's very different than the person who lives across the street. Now, moreover, that data is refreshed fairly infrequently. Annual is most likely the default and maybe some quarterly refreshes. But, you even going back to the pandemic and looking at that in March of twenty twenty versus looking in December of twenty twenty, that would have been very dramatic, and that was within one calendar year. And I just mentioned even within the quarters here with the conflicts that we have from a global perspective and oil prices changing, that does impact how consumer behavior and ultimately some of the wealth across the board is actually impacted. Now the result of this is around twenty billion dollars as a staff from Deloitte is wasted every year in the United States because people are leveraging this inaccurate data. Now windfall came into fruition to help solve this problem. Today, we work with over fifteen hundred organizations across the board. And, really, when we think about the households that we take a look at, we have over a hundred and twenty million households that we're tracking. But, really, what we're known for is affluent US households. We'll define that as anybody over a million dollars of net worth. And my assumption is, because we're here about the top one percent, most of you are also caring about, that specific, demographic as well. Now, ultimately, you know, how folks normally use us is these three components, identification or prioritization. If you can enrich the data, can you sort rank folks up to the top? Now the second component is then grouping folks together. Right? If you're saying, hey. I can actually see that I don't have high, revenue or contributions from a given person, but, ultimately, they still look like similar folks that I've identified. You can group them together and look at cohorts or segments of where you wanna place your bets to determine how you're gonna engage. This is the last component of context. And if it's a very broad set of individuals, maybe you wanna do email marketing. If it's a smaller set, it's personal outreach, and maybe there's something in between for even things like direct mail in terms of marketing as well. So that was a quick windfall overview, but let's go ahead and get to the crux of it, of what it means to be in the top one percent in every state. Now as you probably saw, I've been doing a lot of polls to keep us on our toes today. So let's go ahead, and we will do poll number three, which is gonna be around what does it mean to be in the top one percent in the US. Now we've made this a little bit harder today with very small increments instead. So starting at one million and then going all the way up to fifty, but there's a lot of things in between. So I'm gonna leave that up while you guys are thinking about that and start with just setting the stage from a macro perspective. So we we provide, some other states of the economy. So this is just a snapshot. There are other webinars that we have where we'll go through each one of these. But if you take a look at, you know, some of the things and this data is as of April fourteenth, so a couple weeks back. But, ultimately, what you can see here is that we do have a lot of volatility, of ups and downs that we're seeing. The market's actually up this year. And even the last couple weeks, right, we've seen it go kinda fluctuate, but it's still probably right around the same level. And for us, there is stubborn inflation, especially as we think about oil prices and gas going up, and the personal savings rate is lower than pre pandemic. So it's closer to about, you know, four percent, whereas before twenty twenty, that was actually around eight percent. Now consumer sentiment, if I did pull it, I think this has actually gone slightly down in the last couple of weeks or so. But, ultimately, this is pretty much a snapshot of how we think about the US, which is a mixed bag. Right? If we think about, you know, how people are feeling about this, it is slightly, you know, good in some areas and potentially challenging in others. Now what that really means, if we think about that, is that we're in this k shaped economy. Now you probably have seen some of these stats, but I'm gonna explain it a little bit further of taking a look at specifically how folks are spending in the US economy. And you probably have seen the stats that the top ten percent of earners are now driving half the spending. Now that's on income. But when I take a look at this specific graph here on the left hand side, this specifically speaks around, well, how did savings impact wealthier households, which you could put in the top ten percent of by income? But, effectively, this one point three trillion dollars that they socked away is on their balance sheet. And so this is added to their net worth. They're not making this money every single year, but they're maintaining it. Whereas the other ninety percent of earners tapped into that savings over time, and, actually, anything that we generate during whatever the savings, rate kinda peaked around thirty percent, we've actually dissipated this now in twenty twenty six. And folks are actually spending a lot more on credit card debt. There is harder challenges on kind of the lower ends of the wealth spectrum. But for folks on the upper end, right, that's where we really see the balance sheet. Now I mentioned net worth, so let's just talk about that for a moment. Right? When we think about net worth, that is your balance sheet. And, ultimately, we give you some examples here of, you know, if you had a real estate, you had mortgage, right, you're subtracting all of your liabilities from your assets to get your net worth. So in Windfall's model, as an example, just because you're in that two million dollar property in San Francisco, And if we only knew that you had a one point eight million dollar mortgage, we would consider your net worth to be two hundred k. And so, ultimately, you wouldn't be affluent or a millionaire even though you're living in a very nice property in San Francisco. Now net worth here is modeled, so we have sources of wealth and how we think about, where that that data potentially can get pulled in from as well. But, ultimately, when we think about windfall and for those who are unaware of kind of our modeling, we are a data company. And so when we look at wealth, we have done this for many years, and we're taking a look at asset classes. We're taking a look at how folks are actually stack ranking over time. We have leveraged publicly available datasets like the survey of consumer finances to actually do this analysis. And, ultimately, what you'll see on the, you know, right hand side is that over, especially, I guess, let's just say past nine years, actually, is that we want to make sure that this is fluid and that it refreshes every single week. And so this takes into consideration a lot of that volatility, that I was mentioning a little bit earlier in the market as well as just overall asset classes. And so this is something that we generally have a point estimate, but if you're a customer of windfall, you'll see we have a low bounce and we have a high bounce. We also give you the last calculated date. Now I mentioned the SCF. That is a publicly available dataset that's out there that is put out by the government who actually takes a look at that. And so over the last ten years, we've really taken a look at this to rebuild it every single week and ensure that we have this consistency. This is the dataset that we're driving the rest of the analysis on. So let's speak about why we decided to do this today. So on the right hand side, you'll actually see that we published a blog post in twenty twenty one around this topic. And everybody always asks us the question, well, can you refresh this information? And so here we are in twenty twenty six doing that for for everybody. But there's a couple changes that we've made, as we've evolved as a business and our data has gotten more broad. The first and and this is more of a consideration for everybody on this call. Right? We're talking about the United States here. And so we are still a hundred percent US focused, but we're, focusing on households holistically. So what this means is that, you know, you could have a husband and a wife. They have the same net worth in our models. There's not, you know, one net worth for the husband and one net worth for the wife. So everything's a hundred percent US focused, all based off of a household. Now we did expand the number of households that we had in there. In twenty twenty one, we really talked about homeowners, but we wanted to make sure that we were more broad and had the breadth of our hundred twenty million plus households in this, actual analysis. Now there are a couple of considerations here. We don't really track a lot of folks on college campuses. We don't track ADUs. We don't track, mobile homes or RVs if you're kind of moving around or or more of a nomads because we wanna make sure we understand where your current residence actually is. And the last one here is that when I'm presenting this, you'll see some data that we have across twenty twenty six, and the data is as of April of twenty twenty six, but we'll do some comparisons over the last two years. So we'll look at twenty twenty four to twenty twenty six versus going fully backwards to twenty twenty. I'll have one slide on that. But, you know, we're gonna take a look at more recent changes versus looking at the last five to six years instead. Okay. Cool. And as you're thinking about that, just in the back of your mind, why does this matter? It's because when you think about your own dataset and when you think about how you're gonna form your go to market, a lot of people were thinking about, is my strategy correct? Right? I think that was the third number, question of in terms of why you joined the webinar. Well, even if you think about trip planning, if you think about, where people have moved to in the past, is there other things that you can start to figure out? So put this in the back of your mind. Park it there because we'll we'll come back in terms of that for for some of the strategies that we we would recommend here. Okay. So I will get into the top one percent, and I'll talk about how this is holistic over time versus the snapshot of what it looks like today. So for us, when we think about wealth in the US, we really take a look at and this does go from twenty twenty all the way up through twenty twenty six here. We have in affluent households, almost doubling the number of affluent households in the United States. So that means that being over a million dollars in net worth, you actually almost have two x number of households that you had as of March of twenty twenty. Now those folks have increased their wealth. This is the k shaped economy that we were talking about. While while they have not necessarily increased by a hundred and sixty one percent, they've actually socked away a lot of that wealth. And now close to eighty percent is held by high net worth households. Not the top one percent, but by high net worth households here specifically. So where is that being accumulated across the country? We'll get into that in about three slides here. But for us, right, I'll give you what it looks like across the US as a snapshot right now. So let me go ahead, and I'll get that poll question up real quick here again. So for folks, who were looking at this, a lot of people said fifteen million. I think fifty million was the number one answer. We had twelve. We had ten, you know, somewhere in between. So, you know, this is a mixed bag, but I would say fifty million was the the the winner here. Well, we looked at this quarterly from twenty twenty four to today, so just as I mentioned last couple years here, and it's actually closer to about ten million dollars. And so you can see it's fluctuating on a quarterly cadence a little bit, as I mentioned. Right? It does change over time. But for those that guess about ten million bucks, like, good job. That's that's approximately correct across the entire United States. Now this is up from twenty twenty, which was around six point eight million dollars, which represents about forty two percent increase, just to be in the top one percent. So in order to be in this echelon across the US, you actually have had to grow your wealth pretty considerably over six years five to six years. So where is that wealth growing, or where are those new households? This is probably the last one that we have from twenty twenty to twenty twenty six. But if you look at this, what we're showcasing is new high net worth households that have been actually created across the US. The darker the blue, the more households are created, and the reduction is in this orange instead. You can see that most of the US has seen an increase, although there are these pockets where you've seen decreases. Now it's concentrated, though. If you look around the coast, you can see here on the northeast, on the west coast, there's some concentration here, and there's other ones that are in urban areas instead. But that's pretty natural. We did see a shift back to the urban areas and suburban areas post pandemic when folks, moved back. But you can also see that, the coasts seem to be winning. Now I'm based in the Bay Area. As I mentioned, there is still a lot of increases here on the bottom of the peninsula, but the rest of the Bay Area actually have seen some migration out of it. So that is something to at least consider or think about is understanding that. We'll have a snapshot on that in a couple of moments. Now the other one that we always get asked about is, like, well, where are the billionaires, and where do they live? Because they attract wealth. Right? Well, potentially. And, again, this is based on their primary residence. A lot of billionaires have properties all over the place, but this is where we believe they spend the majority of their time. And so you can see it is in those specific major metropolitan areas, Florida, New York City. We see the Bay Area. We see LA, in there as well. So that is something to at least think about. Now there is a billionaire tax, that I believe will be on the California ballot that has been making a lot of noise. So that potentially could have an impact in wealth in California holistically, not just because a couple billionaires are leaving, but because then that would also attract others to migrate away as well. Okay. So let's take a look at the top one percent by state. What does it look like now? And so on this next slide, I will keep it up for a minute, so that if folks, do wanna take a screenshot, you're more than welcome to do so. We're gonna publish the these stats, but in a couple of days. So here are some of the stats here. This is listed by alphabetical order, and then we have the net worth, in yellow specifically, and then we have the me median value next to it. So you can see the comparison, across the board. And so this will be a little bit more of an eyesore here, as you as you take a look at it. But this is, Alabama through Kansas right here. We'll have Kentucky through North Carolina. And then finally, we have North Dakota through Wyoming. Now I'm going point out a couple of different things, but on subsequent slides we have the biggest winners and least biggest winners probably since wealth has increased in the US over the last couple of years. But what you can see, especially in a place like DC, there's a pretty wide swath between the top one percent and what the median net worth is. In fact, this is the most dramatic one across the board. Now if you take a look at some of the other folks here, when we look at places like Hawaii, they take the winner of having the highest net worth to be in the top one percent. It's not California, which close, but it is Hawaii. And then looking at other places that folks usually care about, we can take a look at Texas here, and we can also take a look at New York as being kind of in between. Cool. So I'll keep it here for a moment. Now if we think about the biggest winners in terms of absolute net worth gains, we're gonna do both. We're gonna do one from a net worth perspective, and we're gonna do the next one on a percentage basis. If you have a higher basis, meaning that your your nominal net worth is higher, if you increase it by the same amount as somebody who has lower, obviously, the percentage increase is gonna be a lot higher. But, that doesn't necessarily mean that you would be in the biggest winner category. So we're just looking at absolute net worth growth here, again, summarized with a yellow column of, like, what we're specifically looking at. So interestingly, while I didn't even mention Utah, Wyoming, or Idaho on the prior slide, those are the ones that have seen the largest increase in overall net worth growth from just a pure dollar figure. So if we had to increase by about three million dollars holistically across the United States, these folks actually increase more than that. These other ones increase slightly lower, but remember that this is where people have their primary residence, not necessarily if they specifically have a property in Idaho itself, and they might live in Texas. So the other things that we can see is that maybe there is some more affluence in migrations. A lot of folks have been talking about that migration to Texas as an example, maybe away from California, or there has been a lot of folks going into places like Maine as well that we have specified in prior webinars. Now if we take a look at this from a percentage perspective, you can see that there are some differences in deltas here where you'll see New Jersey is not gonna actually appear on this next chart. They're below this twenty seven percent growth holistically. And so what you can see on the the left hand side is that most of the players, especially at the top, right, when we took a look at, you know, Utah, Idaho, Wyoming, those were the the top three, and I think Texas was number five, and Maine was over there as well. But, ultimately, they're just switching a little bit of that order, but that's the percentage growth. Now what we do see in terms of the sort ordering is that the Midwest states are starting to take over. Again, if you look at that relative baseline of, like, where they started versus the increase, this is a very small increase comparatively to a four point six million dollar jump up instead. Now for the other states where they're not growing as much, is the inverted table of the lack of growth, I would say, is there was only really two states in the last two years that saw a decrease. Even though Hawaii was number one of an overall state, they declined about a million bucks. Now Oregon also declined fairly negligible, right, like, if you take a look at it. But in general, here, you can see California did increase, but it's it's fairly muted comparatively. Like, this is still a lot of money, if you take a look at it. Right? But we haven't seen as much wealth creation as we probably saw in Utah or Idaho instead. These are some of those insights as we've taken a look at. Now one other thing that we want to at least showcase is some of the delta in terms of how the top one percent from a psychographic or their interests differ from the general US population. So we took a look at the top one percent across the US, and this is not state state specific, but we wanted to take a look at that with the positive differences and then the negative. So, like, where they over index versus where they under index. Now, unsurprisingly, you know, as you take a look at this, you'll see that, you know, the top one percent over index on financial investments. They also care about collecting as well as home improvement. So that is something that, you know, as you take a look at some of these things, that probably makes more sense, especially to market or, you know, personalize associated with that. Now on the flip side, if you're going over to some of the largest negatives, right, they're not necessarily looking at the way that people commonly live, and understand how to cut corners or think about that. They're not thinking about sweepstakes. That kind of makes sense. And they're less religious than the general population from a holistic perspective. That doesn't mean that every single one is, but just as a population or a segment, they're a little bit less religious than the US population. Now what if we wanted to dig a little bit deeper? These are some things that are not gonna be in the blog post. So since you're here, let's let's kinda dig a little bit into some of these stats. Now we we work with a lot of folks that talk about, you know, people that have just recently moved. They've also just purchased homes, or a lot of new cycles are around, you know, home buying affordability and people staying in their homes for a longer period of time because they might have locked in a lower interest rate. Well, we wanna take a look at that. And, yes, they have enjoyed more wealth as an overall class. Now this is not the top one percent, but this is just talking about wealth holistically. And so if you take a look over the last several years, we can see that this has increased by from twenty twenty four to twenty twenty five, close to a hundred and twenty k or so. Now what's important about this is that it's not just real estate values. Right? If you think about that, when we look at inflation, when we think about, you know, the the asset growing, that could probably account for it. But what you can see here is investable assets. Investable assets is your portable liquid, you know, cash that you might have on hand. And this has not stayed flat right over that time horizon, but has also increased as well. And so they're not in the top one percent, but they are enjoying this more holistically as a as a segment of the population. And why we bring this up is because multi property ownership is also something that affluent US households take a look at quite a bit. So we track this. Again, we we mentioned that in terms of people who might have properties in Aspen, but they live in New York, and maybe they have a property in Florida. There's snowbirds. Right? There's a ton of information like that. So on the right hand side, the top one is the year on year growth of property owners and looking specifically at one to five million. And very similarly below, we have the five million dollar plus. So we differentiated high net worth into two categories here just to take a look at the differentiation. And what you can see is that, overall, on the lower net worth side, right, you're seeing that they're mostly owning one property. Right? So bay basically, after we had the pandemic, maybe they had that a property out in the country. They most likely sold it, and they came back. Now whereas if you look at the folks that have five million dollars plus, this is pretty consistent over time. Right? And so, ultimately, that's really where we're seeing some of the changes here. And that's, again, as a category or grouping. We're we're gonna show you a little bit more about how this is different on a per state basis in a moment, but that is that is something that does come up and is impactful to at least understand of where these folks actually might reside. So for us, the next thing that we think about is like, okay. Well, are these vacation homes, or are they rental properties? Right? Well, at the end of the day, when we're looking at this, we actually understand vacation property ownership versus having a rental property ownership or investment property. And very similarly to that trend, vacation home ownership did decline. So this is very similar to the last slide, but it's a lot of folks moving back to their primary residence. Maybe debt has gone higher, and depending on their investment structure or their purchasing structure, they wanna take a look at that. And this is something, again, since twenty twenty two, been pretty consistent in our dataset. The last one that I'll show you before we go into some state specific items are gonna be around like, industries or sectors over the last couple years as well. And we're just looking at an overall, growth percentage. So we we took a look and sort order by growth here. Sorry. I should've put this in yellow of, like, what we were trying to take a look at. But this is saying, hey. How many folks were above from a high net worth perspective? And then, ultimately, what was that median net worth that we're taking a look at? And so it's pretty interesting. Right? As you take a look, legal services is is pretty in there. Private equity is in there as well, and those will be normal. What you can see, though, is that we don't really see tech on the list here, specifically. It might mean that the growth is probably muted or it's fairly flat. Again, that Bay Area consideration that I even mentioned a little bit earlier, where tech has its hub. But across the board, as you're thinking about combining not just wealth but other attributes or other data points, this can really start to help you think through, okay. Well, what can I mix and match together? Let's, also sorry. Just to make a note here. Oil and gas is on the list here as well, but industries could be impacted by this in twenty twenty six. So as we're taking a look at this, right, the snapshots or the growth over time is gonna be something as well that you'd wanna take a look at on a monthly, quarterly basis as you're determining your strategy. Okay. Last poll here. And so, you know, I probably have tipped it a little bit, but let's go ahead and, do the final poll, which is around, like, well, how similar are these top one percent across states? And I'll let everybody take a look. So similar. You know, there are very big differences. We put metro versus rural versus just thinking about states. So we'll let everybody kinda answer just for a moment here. Cool. So gonna share those results real quick. And, they're fairly different based off a region or con or of the country. They might be very so I you know, it's all of the above, to be very honest with you. Like, they're not very similar. There might be differences, but, again, it does depend, right, across the board. So as we take a look at that, we chose Colorado and Louisiana, far enough from a geographic perspective. And on the left hand side here, the top one percent from a net worth perspective, we just purposed this, but then added some more information for folks here. So the million dollar plus population out in Colorado is larger than Louisiana holistically, but you can see that it's almost three x the wealth to be in that top one percent. Now, moreover, even though we said multi property ownership was pretty pretty consistent, we had that one to five and five million dollars plus, in this scenario, folks in Colorado actually had less multi property ownership than Louisiana. Well, that's kind of interesting. Right? And they had more rental property ownership than what you could probably see. But you can also determine other impacts. Folks in Colorado are a little bit more philanthropic. They also give more to political contributions. So when we look at other potentials, now this for financial services or wealth management, right, if you have a trust or your sophistication, of course, as you go up the totem pole in terms of net worth, it makes more sense to have trust versus, you know, at lower affluence levels where they might not necessarily wanna pay for that at that moment. So in addition, we also try to say, okay. Well, what does the psychographics look like for Colorado versus Louisiana? So this is where it is a little bit of more of an overlap. We couldn't find that much. They like sports. They collect. They still have, you know, interest in in a bunch of, other considerations here as well. But, ultimately, for the negative side, also not that big of a deal. So there are slight differences between Colorado and Louisiana. Especially if we look at it from a financial perspective, there are some differences from a psychographic or their interests or hobbies. There might be more overlap than what folks probably think. Now I will bring this back in, because understanding where that person's primary residence does have a large impact in terms of ranking and looking at this. We'll take a look first of the most populous state in the country, which is California. If you only include the primary addresses so we don't have any vacation homes in here that people might own that would be seventeen point five million, including anybody who doesn't have their primary residence in California. But then improving it, actually increase the net worth to be top one percent to seventeen point eight million. Okay? That's not that big of a deal. Right? You know, it's it's probably, like, less than a couple percentage points. Now if we look at Idaho, Idaho was at eight point two million. Now if we took a look at anybody who owned a property in Idaho and did not understand where their primary residence was, that actually shoots up to eleven point five million. So that's a much larger increase, and ultimately the sentiment around who's living in Idaho versus who might actually just have assets in Idaho instead. And lastly, this is not just about taking a look at your state. You can also look at metros. As I mentioned, I was gonna take a look at the Bay Area again. Now it's wealthy on paper as we took a look at, but even just driving around the bay could potentially change. Again, this is the median net worth. And if we're looking at a place like Los Altos, which is one of the most wealthiest parts of the United States, three point eight five million is the median. That's the median net worth, which is pretty high compared to taking a look at the other part of the Bay, where the median net worth is closer to four hundred ks. Now that looks much closer to the US population average instead, but you can see across the Bay Area, this does differ even within just taking a look at the given state and in an area that we normally, take a look at as being fairly wealthy. Okay. Cool. So I'm gonna kind of go through these next slides a little bit more quickly so at least I can show you how to activate this. So what do you do with these insights? Right? I just gave you a lot of information. Like, that doesn't really, like, help you too much. I mean, it's interesting for sure. It's it's definitely curious. But you wanna be able to get this data. And a lot of folks already use one plus different sources, so you wanna get it into your workflows. And you wanna be able to understand how to actually take a look at that in particular. So that's where we're gonna go next as we're talking about these various strategies around ultra high net worth and high net worth households. But before I get started, there is a caution. And I know we're biased here, obviously. We have our own data. But selecting the wrong data can be costly for your overall processes. And I'm not talking about just the expense of the solution, but I'm also talking about the opportunity cost and the human output or throughput that's necessary. Let's just imagine, again, if we have provider A, and, again, you have somebody that comes in here with a range. We actually know that this is probably not gonna be true, but we know they're philanthropic, and we don't really know their job level. Ultimately, everybody is trying to build more of a personalization engine or a context. And so understanding prospects, determining, okay. Well, I'm not a hundred percent sure. Well, let's send them an email. Okay. Actually, I put them in the wrong segment. They're dormant. I'm gonna try and reengage them. The data's stale. I didn't update it because I don't have it updated all the time. Oh, it took close to a year. And, by the way, the person who I still ended up selling didn't have that great of an experience. Ultimately, we think about speed to value a lot. If you have much more precise information, if you're able to then determine additional attributes, all of a sudden, you can qualify, you can outreach, route it correctly, and then ultimately win. And so these are the types of things that I think most folks wanna do with this data. And so when we go through and and talk about what that looks like, well, we really wanna start first with looking at market intelligence. Start with this macro view for your overall strategy. And so what we think about here is sizing the market. This is not even your data, but just saying, well, how many many high net worth folks are there in these various states, in these various locations, in regions, in cities? Well, then where do you wanna determine where you wanna go? Is it growing? Is it shrinking? Like, how does that look over time? And then ensure that even within that location, if you have a penetration, well, how do you make sure that you're targeting the right people at the right time? As an example of that, we call it exploratory data analysis. You can think about just market insights. But being able to take a look at your existing clients and overlaying them in Florida versus looking at just overall market opportunity, we could first start here and then overlay your locations and start to really understand, well, maybe there's somewhere else that you wanna open up another office or potentially go visit. Now those are the types of things that start to come into place. But, ultimately, why are we still doing that once we understand market insights? Right? You've you've kind of and that was one of the questions. It's like confirming that, directionally, my strategy is right. But you really want to enhance your database so you can sort and rank the consumers. Again, seventy five percent plus of you already do some of this stuff. So if you have a likelihood to respond and a likelihood to convert, this could be likely to donate, likely to transact, likely to purchase something. Right? Every single one of these gray dots, we're trying to flip over and figure out if it's a green or is it red or it's a maybe. Right? Well, that's not great. That's not super efficient. What we really wanna do is sort order the database to focus only on the greens, maybe some yellows, but definitely not any of the reds. So that is what data and AI does, and that could be your information. It could also be augmenting it with third party data, which is what we would advise because you don't know what you don't know. And that turns the data into action. So what you can think about is that you have all of these various attributes or data points that you can start to enrich. By being able to do that, you can segment your population, and then that actually drives the ultimate specific routing, that specific message, whatever you need to do for your next action. And this does drive better outcomes. Right? You're able to personalize and create that context and measure that that segment is still performing once you've set it up correctly. Right? You have to set up the segment with the same criteria to actually measure that over time. And, of course, there's two different paths that a lot of folks are thinking about here. We're about to come out with this just in a moment. But if you think about real time and batch process, if you're a Windfall customer, our Windfall API is actually live as well, And that's something that you could do on a lead form, make sure that you have a response here, and then route it as quickly as possible. Now we do batch processing as well, which means that we're integrated directly into your CRM, into your database, data warehouse. And, ultimately, this is where we're talking about the various records that you've taken a look at. Instead of doing it one by one, let's make sure that we do the full swath of it so we can really understand segmentation and, ultimately, reactivate or group them together for new leads to to put them into the right cohort. Now I'll I'll I'll kind of speak a little bit more on terms of, okay. Well, once you've had that enrichment, what are you gonna do with it? Well, you gotta zoom in. You gotta start playing with the data. Right? It's it can be quick, but you need to take a look at your territories. Is there enough in that region? Do we believe we can win the market? Are we not doing as well? Have we actually personalized and provided that context that we talked about? And now you can actually choose the right markets to double click on and pursue those bets. The last thing that I'll mention, though, is that sometimes if you put this in a CRM and you put all this data together, what is a human being gonna do with that? This is where generative AI and other use cases actually are super helpful. Providing your frontline team things like dossiers where you can take a look at an individual, you can give them the LinkedIn URL, summarize things, and give them outreach strategy, huge. And this takes less than a couple of minutes to actually generate. Now there's an AI score here on the right hand side because, ultimately, wealth is a qualification. It's not the only factor. As we just talked about with Louisiana and Colorado, we have differences here. And so, ultimately, when you think about this, it could be across the board where you have AI, and this is predictive AI, to determine if you have two different folks in your database, prospects, leads, whatever else. Well, let me take a look at their net worth. They both had good engagement. That's from your CRM or first party data. One's a boner. The other one's not. They're both philanthropic. One owns multiple properties. They're both qualified. Right? If we think about this, we we wanna talk to both of those individuals. But if we only got to choose one, who would we choose? Most people would choose the person on the left hand side. By looking at predictive modeling, though, you would wanna see, is the conversion in the next three months? Well, go after the person that's actually worth five point three million dollars instead. That's how we think about the one two punch. Now when I look at that, and you're like, okay. Well, how do I do that? That's that's a lot of the predictive modeling that you can utilize leveraging geo signals as well. In fact, if you look at the left hand side, we think about this as saying, let's look at your database. You have folks that are in Colorado. You have folks that are in the northeast, and you can probably make this story what what resonates with you. Well, the centroid represents your best customers. The closer you are to that, the higher likelihood there's conversions. Now there's gonna be some overlap between Colorado and the northeast, but you can see that there's some folks in the northeast that are simply not like the folks in Colorado. We can use this to sort order the database and effectively rank those individuals that you would wanna retarget. Now what's really cool is you're like, well, I wanna also do this for digital targeting, direct mail, increase the population for marketing. We'll call that net new acquisition instead. You can apply that same model and then overlay it into the US population. We call it the windfall population here instead. So once you've understood the market insights, once you've started to enrich your data, once you've determined that, like, hey. From a predictive perspective, I can really start to hone in on it, that's where you can drive new business at the right time. And this is net new business. Right? So this is where we're taking a look at a subset of the database. You can either just segment and say, hey. Based off my market insights, I wanna go after doctors and lawyers in the northeast that are worth at least five million dollars. Or, hey. You know what? I wanna use that predictive scoring, and maybe I wanna overlay it with lawyers and doctors. But at the same time, I'm okay with it. As soon as you have that audience, we actually have integrations into social digital platforms. Or if you do direct mail today, we can help you retarget those folks, or we can help activate for net new. And what's really cool about it is then because Windfall is the data layer, only high net worth or ultra high net worth are gonna see your ad on Meta, Instagram, whatever platform, you choose to send this data to. Cool. So with that, I know that, some folks had some questions here, but, I'm gonna do a quick demo just really, since I know I have some folks here, just to showcase what it looks like. So please do, put your, questions in the q and a box if you have them. But what I'm gonna show you first is we're gonna take a look at market insights. And, specifically, this is the new product that Windfall came out with a couple weeks ago. So we got asked a lot of questions around, well, how many high net worth individuals have recently moved? And can you actually show me what that looks like? And how many customers do I have? How many households are there? And what's my overall penetration? And in fact, in this demo environment, we have folks, five million, ten million, hundred million, but let's just take a look at the folks that are five million dollars plus. Well, in this scenario here, five million dollars plus, it was already calculated. We can see it changed. And moreover, you can actually click into that and see below the county level information with their average net worth, penetration, total households, and where you have the number of customers based off of the definition you have. You could always create new ones. And, again, it's not just about wealth. We have career data. We have recency triggers. You can do the entire United States or specific, states that you have, or you can build this out yourself. And we have so many different attributes that you can actually take a look at and segment off of that these market lenses really help you understand that. Moreover, you can start to go through and layer on your customers so you can now dig in and actually see the visit physical locations that you might have around those specific locations. So we don't have anyone in in Maine, but I think I did have some folks here in New York as an example instead and Massachusetts. Right? So you can see that the overlay of the locations really shows you where your potential penetration looks like. Okay. Cool. So we're like, awesome. This is fantastic. I've now done a bunch of research, and these are reports that get generated and sent to me every month automatically for my CFO, my CEO, like, anybody who's on the team. What do I wanna do next? Really what I wanna do next is that I want to take a look at my own data. As soon as I take a look at my own data, I can start to understand this a little bit further. So let's pull up that view. And this is another demo environment where Acme Inc and it if we go to discovery, a couple of different things here. One, we have AI recommended segments. We think about this as saying, you don't know where to go next? Well, we have snowbirds. We have other folks that have recently changed companies. We have ultra high net worth folks, luxury boat, plane, and car owners. Like, all of these are things that you can automatically do because might not necessarily know where to start. And in fact, when we're looking at the database, this is where we can take a look at segmenting or net new. And segmenting can take a look at any of your data, so we can take a look at all of your prospects. We can look at anybody who maybe they live in New York, but they also have that property in Florida. And, by the way, that net worth is greater than or equal to two point six million dollars. Now as I mentioned, Windfall has a multitude of different data points, and so this data can go to your CRM, or you can just segment directly in here, suppressing your customers. That's already done. And then we have a segment that we're gonna name and actually create. I've already done that. So I'll show you what that looks like specifically here. Now let me take a look at maybe folks that are worth ten million dollars that have children and are located in New York, New Jersey, and Connecticut. Very quickly, we can actually take a look and say, yep, this includes Connecticut, New Jersey, and New York. Their children presence greater than or equal to ten million bucks, and they're all prospects. You can see it zoomed in to that view that I had in one of the slides. Now there's a couple of different things that you can do here. One, as an example, this demo environment has Salesforce. So if you wanna send this data back into Salesforce campaign if you have Salesforce, by the way, this is a new feature that we launched a couple of months ago. So you can actually start to measure the impact of it. We can activate a marketing campaign, so we can send it to Meta. We can send it to Google, YouTube, or we can just export the data directly into a spreadsheet if we really wanted to. But a newer feature that we release also connects these together. Right? So we can take a look and actually view the profiles. And so what this does is really quickly, this is the data coming from your CRM. But on the right hand side, this is where we say we have wealth information created. Now this is a pretty, you know, wealthy segment with a lot of billionaires here as well. Right? But if we started to go through that and we just even clicked on Richard here, we get a better sense of the information. And we can see his LinkedIn profile, his URLs. We can also see no transaction data, but we can click generate dossier just in a quick moment here. And so with all of that information, I've been able to actually do what I showcased you in our deck in about four minutes. And so this really simplifies your broader approach to the high net worth market and ultra high net worth market, and these dossiers will then enable your team to really start to understand this further. And so here's an example of this dossier, which we can then print and make it really nice for anybody on the front line to take a look at this as well.